This study captured the perspectives of 887 working adults to explore views of professionalism, authenticity, and effectiveness of AI-generated messages. With a 3 (message type) × 2 (disclosed vs. undisclosed) × 2 (ChatGPT-generated vs. Google-generated AI messages) design, professionals generally view AI-generated content favorably in all conditions. Across all messages, professionals consistently rated the AI-generated messages as professional, effective, efficient, confident, and direct. They rate sincerity and caring slightly lower in some disclosed conditions, particularly for ChatGPT-generated messages, suggesting the importance of tool selection when using generative AI for workplace writing. Those professionals who use AI more frequently for work are more likely to view AI-assisted writing as authentic, effective, and confidence-building. Implications for teaching business communication, including the need to address AI literacy, and suggestions for future research are provided.

Artificial intelligence assignments lead this article’s 11 teaching innovations selected from the My Favorite Assignments presented at the 2023 Association for Business Communication’s Annual International Conference held in Denver, Colorado. USA. Pedagogy presented here also includes ideas to enhance student engagement and techniques to transform learning via gamification.

The first time I recall encountering artificial intelligence was in the early 2000s while working in a recording studio. After singing a take of a song, I watched as an engineer opened a plug-in called Auto-tune and then listened as he worked on tuning my vocals. I recall him explaining to me that the vocal had to be pretty close to the note I was trying to sing, otherwise the tuned version would sound fake. He demonstrated by tuning my vocal too sharp and then too flat. The sound of the stressed vocal created a distorted tremolo effect, with maybe even a bit of delay. It no longer sounded like me. It sounded like a robot who was impersonating me. I bristled. "No, not like that," I said uncomfortably laughing. "That doesn't sound like me."

Our First-year Writing program began intentional student engagements with generative AI in the fall of 2022. We developed assignments for brainstorming research questions, writing counterarguments, and editing assistance using the AI tools Elicit, Fermat, and Wordtune. Students felt that the tools were helpful for finding ideas to get started with writing, to find sources once they had started writing, and to get help with counterarguments and alternate word choices. But when given the choice to use the assistants or not, most declined. Generative AI at this stage is unreliable, and many students found the tradeoff in reviewing AI suggestions to be too time consuming. And many students expressed a preference for continuing to develop their own voices through writing. Our experience in engaging AI led to the creation of the DEER praxis, which emphasizes defined engagements with AI tools for specific purposes, and generous use of reflection.

We share our experiences working with large-language model generative AI for a full semester in a professional writing course, integrating it into all projects. We discuss how we adapted our teaching, learning, and writing to using (or purposefully not using) AI. Issues we discuss include balancing integration of AI to avoid potential overreliance, the importance of centering authorial agency and decision-making, negotiating grading and evaluation, the benefits and drawbacks of AI throughout the writing process, and the relationships we build or could build with AI. We close with recommendations for faculty and students.

To be editors in what is now the Age of Artificial Intelligence is not without a feeling of jamais vu.Our practices are predicated upon the existence of the author, which has been called into question by large language models.Although artificial intelligence is not an author because it cannot produce an original text, its texts are, or soon will be, indistinguishable from those produced by an author.In other words, if the original text and the unoriginal text are identical, then any author is simultaneously a nonauthor.We see this paradox, in its mix of the strange and the familiar, as part of an epistemic transformation of our relationship to the text.This paradox is sustained by a cultural resistance to our changing understanding of authorship.Despite the prominence of such essays as Barthes' (1977) "The Death of the Author" and Foucault's ( 1978) "What is an Author?", which dispute historical assumptions about the author as the origin of the text, these theories have never made "the pedagogical turn" (Graff, 1995) into a praxis for relocating the text's origin.Writing is still widely taught as a response to prompts, which locate the origin of the text inside the student.This method of instruction directs attention to the text as it tacitly perpetuates a belief that writing well is a "gift" innate to the individual.Michael Palmquist and Richard Young (1992) observed that this belief does indeed reappear in the writing classroom and pointed out that students who consider themselves ungifted may not pursue opportunities for learning, given the futility of trying to improve an ability they do not possess.There is a symbolic violence to this process by which students embody a belief that they cannot write but are nevertheless confronted with prompts to revise their writing.Consequently, they may avoid revision because they see it not as practice for improvement but as "punishment" (Downs, 2015, p. 67) for being wrong.This symbolic violence can, however, be converted into critical thinking if the text's origin is relocated.Consider an instruction to produce a piece of writing not by responding to the prompt but by replacing its interrogative pronoun (what, which, who, whom, whose) with its antecedent.The student thereby locates the origin of the text outside themself in a preexisting first draft they make present in writing.The instructor, in turn, decides what part of the text is still missing and adds to the draft the interrogative pronoun or proadverb (why, where, when, how) in a prompt for revision.The student, in turn, replaces the interrogative with its antecedent to produce a second draft.And as an interrogative can be addressed to any draft, revision, as a reversal of proformation, is the disclosure of a text that ever exceeds it.Through revision students gradually embody improvement as "a feel for the game" (Bourdieu, 1998, p. 25), a practical sense of which words go where, and through prompts they reflect on how their manipulation of these words enacts meaningful

Vivian Kao is associate professor of English and director of the first-year composition program at Lawrence Technological University. She teaches courses in writing, literature, film, and the intersection of technology and the humanities. Her courses often feature multimodal assignments that challenge students to think about composition as activity, experiment, and craft. Her other publications include an account of students exploring essay form by building three-dimensional structures, and a forthcoming visual essay on virtual museum exhibits created in response to modernist literary texts.Jessica Masterson is assistant professor at Washington State University Vancouver, where her research concerns the intersections of language, literacy, and democratic teacher education.Sarah Moon is assistant professor of humanities at Massachusetts Maritime Academy, where she teaches composition, writing about literature, environmental writing, and American theater. Her scholarly work has been published in Community Literacy Journal, Literacy in Composition Studies, Journal of Multimodal Rhetorics, and Center for Sustainable Practices in the Arts Quarterly. A playwright, she was the 2023 artist in residence for Eastern Connecticut Center for History, Art, and Performance, where she developed the original full-length drama Apostates.Molly Parsons earned her PhD in English and education at the University of Michigan. She is currently assistant director of the Center for Research and Writing at Keene State College, where she has the privilege of learning alongside talented undergraduate tutors. Her research interests include the ethics of writing center practice, grammar instruction for tutors, and, presently, the implications of artificial intelligence for tutoring and teaching. Find her other work in Praxis: A Writing Center Journal, Writing Lab Newsletter, and Another Word, a blog from the University of Wisconsin-Madison's writing center.Kevin Piper teaches literature and composition at Madison College and is an honorary fellow at the University of Wisconsin-Madison, where he received his PhD. His recent work looks at how teachers can use student feedback to improve their practice. His literary scholarship has spanned a wide range of areas, including ethnic and Indigenous literatures, postsecular literature, and literary modernisms. He can be reached at kcpiper@madisoncollege.edu.Malini Johar Schueller is professor in the Department of English at the University of Florida. She has been the faculty advisor for Students for Justice in Palestine on her campus for many years and is a member of the organizing collective for the US Campaign for the Academic and Cultural Boycott of Israel. She is the author of several books, including U.S. Orientalisms: Race, Nation, and Gender in Literature, 1790–1890 (1998), Locating Race: Global Sites of Post-Colonial Citizenship (2009), and Campaigns of Knowledge: U.S. Pedagogies of Colonialism and Occupation in the Philippines and Japan (2019). She has coedited Exceptional State: Contemporary US Culture and the New Imperialism (2007) and Dangerous Professors: Academic Freedom and the National Security Campus (2009). She is the director of the award-winning documentary In His Own Home (2015) about police brutality and campus militarization. In 2019 she was selected to participate in a Faculty Development Seminar by the Palestinian American Research Council. Currently she is working on an essay collection, From Palestine to You. She teaches courses in comparative settler colonialism, including Palestine, and courses in postcolonial theory, Asian American studies, and US imperialism.Elina Siltanen was university lecturer at the Department of English, University of Turku at the time of writing this article, and now works at the University of Eastern Finland. Her research focuses on contemporary American poetry, more specifically on the role of affect in reading complex literary texts, and her article is a part of her research project “Difficult Relations: Reading for Emotion in Recent American Experimental Poetry.” Recently, she has published articles on the connections between conceptualism and confessionalism in poetry in the Journal of Modern Literature and on metamodernism and New Sincerity in English Studies. She has a double doctoral degree from the University of Turku and Luleå University of Technology.D. T. Spitzer-Hanks is an early-career researcher interested in critical composition studies and in transatlantic critical classical reception in the long nineteenth century, specifically in North America and the United Kingdom. Spitzer-Hanks is particularly interested in analyzing how patterns of communication and perception create social structures in which inequity is fostered and sustained and seeks to find ways to intervene in such processes both as a scholar and as a member of society. Trained in gender and ethnicity studies at the University of Utrecht in the Netherlands, Spitzer-Hanks earned a PhD in English studies from the University of Texas at Austin. In their private life, Spitzer-Hanks enjoys gardening, parenting, and running from their anxieties.

Employers are increasingly turning to innovative artificial intelligence recruiting technologies to evaluate candidates’ online presence and make hiring decisions. Such social media screening, or social profiling, is an emerging approach to assessing candidates’ social influence, personalities, and workplace behaviors through their publicly shared data on social networking sites. This article introduces the processes, benefits, and risks of social profiling in employment decision making. The authors provide important guidance for job applicants, technical and professional communication instructors, and hiring professionals on how to strategically respond to the opportunities and challenges of automated social profiling technologies.

In this teaching practice article, we discuss the possibilities of integrating AI into the writing classroom utilizing prompt engineering techniques. We propose a strategy for prompt engineering in which we see AI as an audience and interlocutor during the invention process. We consider using the method in preparation for argument composition and with that we propose an ethical model for teaching writing based on a view of rhetoric as both technê and praxis. To draw attention to the ethical question in relation to human—non-human interactions, we use as metaphor for AI tools the image of Klara, an android who serves as a children’s companion in Ishiguro’s novel Klara and the Sun (2021).

The primary purpose of this study is to investigate the degree to which register knowledge, register-specific motivation, and diverse linguistic features are predictive of human judgment of writing quality in three registers—narrative, informative, and opinion. The secondary purpose is to compare the evaluation metrics of register-partitioned automated writing evaluation models in three conditions: (1) register-related factors alone, (2) linguistic features alone, and (3) the combination of these two. A total of 1006 essays ( n = 327, 342, and 337 for informative, narrative, and opinion, respectively) written by 92 fourth- and fifth-graders were examined. A series of hierarchical linear regression analyses controlling for the effects of demographics were conducted to select the most useful features to capture text quality, scored by humans, in the three registers. These features were in turn entered into automated writing evaluation predictive models with tuning of the parameters in a tenfold cross-validation procedure. The average validity coefficients (i.e., quadratic-weighed kappa, Pearson correlation r, standardized mean score difference, score deviation analysis) were computed. The results demonstrate that (1) diverse feature sets are utilized to predict quality in the three registers, and (2) the combination of register-related factors and linguistic features increases the accuracy and validity of all human and automated scoring models, especially for the registers of informative and opinion writing. The findings from this study suggest that students’ register knowledge and register-specific motivation add additional predictive information when evaluating writing quality across registers beyond that afforded by linguistic features of the paper itself, whether using human scoring or automated evaluation. These findings have practical implications for educational practitioners and scholars in that they can help strengthen consideration of register-specific writing skills and cognitive and motivational forces that are essential components of effective writing instruction and assessment.

Generative AI may significantly disrupt the teaching and practice of business communication. This study of 343 communication instructors revealed a collective view that AI-assisted writing will be widely adopted in the workplace and will require significant changes to instruction. Key perceived challenges include less critical thinking and authenticity in writing. Key perceived benefits include more efficiency and better idea generation in writing. Students will need to develop AI literacy—composed of application, authenticity, accountability, and agency—to succeed in the workplace. Recommendations are provided for instructors and administrators to ensure the benefits of AI-assisted writing can outweigh the challenges.

In the wake of the controversy surrounding the new AI chatbot application, ChatGPT, I wonder how Logie would seek to include this new technology in his work. I ponder this because, throughout the book, Logie presents compelling evidence for why the concepts of invention, composition, and internetworked writing should be embraced and not feared. While some denounce the application and take to social media to disparage the possible negative impact on students, creativity, and composition, ChatGPT, I believe Logie would argue, would be a powerful tool we can implement to become "composers." He believes that through cloud computing services we are now more apt to collaborate, use, remix, and create rhetorical modes that extend far beyond the formulaic argument, therefore we are composers. So, Logie applies the idea of a composer as someone who is a "prosumer" (Toffler). This composer is media literate and transforms traditional rhetorical canons into multimodal compositions such as memes, Google Docs, and digital collages. However, his overarching argument is that internetworked writing tools have democratized writing through that same offering of innovative outlets. His book is arranged in a way that walks the reader through this argument.

I offer a meditation on current challenges faced by literacy educators and researchers and uses those challenges to suggest new directions for the field. Citing the precipitous decline in interest in the humanities and the field of literacy education, I consider the significance of tools such as ChatGPT for the teaching of writing. I explore the significance of out-of-school literacies and the linguistic diversity of today’s students in terms of their implications for literacy instruction. I also remind us of the chilling political climate in which we find ourselves, especially with regard to LGBTQ+ identities. Given these contemporary challenges, I suggest that we in the field of literacy education rethink the nature of writing instruction, restructure our research paradigm to be more inclusive and democratic, and continue to be forceful political advocates for pedagogies, practices, and policies that will ensure a just and equitable literacy education for all.

An experiment in enlisting ChatGPT as a collaborator for scholars who wish to design academic multimedia webtexts.

In this paper, we investigate two approaches to building artificial neural network models to compare their effectiveness for accurately classifying rhetorical structures across multiple (non-binary) classes in small textual datasets. We find that the most accurate type of model can be designed by using a custom rhetorical feature list coupled with general-language word vector representations, which outperforms models with more computing-intensive architectures.

The study explored six ESL university students’ behavioral, cognitive, and affective engagement with e-rater feedback on local issues and examined any changes in students’ engagement over two weeks. We explored behavioral engagement through the analysis of screencasts of students’ e-rater usage and writing assignments. We measured cognitive and affective engagement by analyzing students’ comments during the think-aloud protocol and reflection surveys. The findings indicated that the students had varying levels of engagement with the feedback. Behaviorally, all students used a range of revision operations to address errors based on the provided feedback. Cognitively, some students were more engaged than others. Affectively, students experienced both positive and negative reactions toward e-rater feedback. While some students’ engagement with feedback did not change over two weeks, others’ engagement grew more negative. We conclude that e-rater feedback could positively impact students’ accuracy in local aspects of writing if students are actively engaged with the feedback.

AI-based natural language production systems are currently able to produce unique text with minimal human intervention. Because such systems are improving at a very fast pace, teachers who expect students to produce their own writing—engaging in the complex processes of generating and organizing ideas, researching topics, drafting coherent prose, and using feedback to make principled revisions that both improve the quality of the text and help them to develop as writers—will confront the prospect that students can use the systems to produce human-looking text without engaging in these processes. In this article, we first describe the nature and capabilities of AI-based natural language production systems such as GPT-3, then offer some suggestions for how instructors might meet the challenges of the increasing improvement of the systems and their availability to students.

This article follows up on the conversation about new streams of approaches in technical communication and user experience (UX) design, i.e., design thinking, content strategy, and artificial intelligence (AI), which afford implications for professional practice. By extending such implications to technical communication pedagogy, we aim to demonstrate the importance of paying attention to these streams in our programmatic development and provide strategies for doing so.

As artificial intelligence (AI) automates technical and dialogic processes, technical communicators produce value through articulating complex problems, facilitating new forms of participation, and managing user-generated content via experience architecture. Automated and intelligent agents are least able to grasp the context of experiences, requiring human input/feedback for maximum performance. The examples we trace both prepare communities to embrace AI as part of the available information infrastructure and create an automated infrastructure of intelligent augmented action. Following Star's anthropological investigation of infrastructure, we analyze organizational examples where rhetoric entangles AI, automation, generative design, additive manufacturing, gift labor, and assembly lines.

This study examines links between human ratings of writing quality and the incidence of argumentative features (e.g., claims, data) in persuasive essays along with relationships among these features and their distance from one another within an essay. The goal is to better understand how argumentation elements in persuasive essays combine to model human ratings of essay quality. The study finds that, in most cases, it is not the presence of argumentation features that is predictive of writing quality but rather the relationships between superordinate and subordinate features, parallel features, and the distances between features. This finding has not only theoretical value but also practical value in terms of pedagogical approaches and automated writing feedback.

The rapid, widespread implementation of artificial intelligence technologies in workplaces has implications for business communication. In this article, the authors describe current capabilities, challenges, and concepts related to the adoption and use of artificial intelligence (AI) technologies in business communication. Understanding the abilities and inabilities of AI technologies is critical to using these technologies ethically. The authors offer a proposed research agenda for researchers in business communication concerning topics of implementation, lexicography and grammar, collaboration, design, trust, bias, managerial concerns, tool assessment, and demographics. The authors conclude with some ideas regarding how to teach about AI in the business communication classroom.

This Methodologies and Approaches piece argues artificially intelligent machine learning systems can be used to effectively advance justice-oriented research in technical and professional communication (TPC). Using a preexisting dataset investigating patient marginalization in pharmaceuticals policy discourse, we built and tested 49 machine learning systems designed to identify and track rhetorical features of interest. Three popular and one new approach to feature engineering (text quantification) were evaluated. The results indicate that these systems have great potential for use in TPC research.

Technical and professional communication (TPC) and user experience (UX) design are often seen as intertwined due to being user-centered. Yet, as widening industry positions combine TPC and UX, new streams enrich our understanding. This article looks at three such streams, namely, design thinking, content strategy, and artificial intelligence to uncover specific industry practices, skills, and ways to advocate for users. These streams foster a multistage user-centered methodology focused on a continuous designing process, strategic ways for developing content across different platforms and channels, and for developing in smart contexts where agentive products act for users. In this article, we synthesize these developments and draw out how these impact TPC.

This article uses a machine learning algorithm to demonstrate a proof-of-concept case for moderating and managing online comments as a form of content moderation, which is an emerging area of interest for technical and professional communication (TPC) researchers. The algorithm sorts comments by topical similarity to a reference comment/article rather than display comments by linear time and popularity. This approach has the practical benefit of enabling TPC researchers to reconceptualize content display systems in dynamic ways.

In writing studies research, automated writing evaluation technology is typically examined for a specific, often narrow purpose: to evaluate a particular writing improvement measure, to mine data for changes in writing performance, or to demonstrate the effectiveness of a single technology and accompanying validity arguments. This article adopts a broader perspective and offers a standpoint theory of action for formative automated writing evaluation (fAWE). Following presentation of the features of our standpoint theory of action, we describe our two study sites, and each instructor documents her experiences using the fAWE application (app), Writing Mentor® (WM). One instructor analyzes experiences using the app with nontraditional adult learners to provide career pathway access through a high school equivalency (HSE) credential awarded by successful completion of the GED® (General Educational Development Test) or of the HiSET® (High School Equivalency Test). A second instructor analyzes WM experiences working with a diverse population of two-year college students enrolled in first-year writing. These instructors’ experiences are used to propose two theory-of-action frameworks based on the instructors’ standpoints, with particular attention to fAWE components, pedagogies, and consequences. To explore the representativeness of these two case studies, we also analyze student feature use and self-reported self-efficacy data from a general sample (N = 5,595) collected through WM user engagement. We conclude by emphasizing the pedagogical potential of writing technologies, the advantages of instructionally situating these technologies, and the value of using standpoint theories of action as a way to anticipate local impact.

This book provides a useful and practical framework for professional user-experience (UX) teams and students who need to understand how consumers think. It has achieved its purpose in the following ways: educating designers about the Six Minds of Experience Framework; showing researchers how to uncover new insights from customers; and demonstrating how to use the Six Minds of Experience framework to enhance the design for products and services. This book sets itself apart from the other technical communication books that discuss understanding audience experience because the author suggests that UX is multidimensional and multisensory, and that looking at more than one cognitive process will unwrap many more facets of the consumer’s thoughts behind the experience. The book concludes by leaving designers with a thought for the future. The author briefly discusses the history of artificial intelligence (AI) and its current evolutionary stage as Siri, Amazon Alexa, Google Assistant, etc. He argues that Six Minds can be a framework to explore how machine learning and AI can support humans by augmenting their cognitive abilities. Whether in the workplace or the classroom, this short book will supplement UX designers and technical communication students in exploring what it means to truly know the target audience.

This article introduces a Special Issue that gathers a collection of effective tools to promote the teaching and learning of writing in school-aged and university students, across varied contexts. The authors present the theoretical rationale and technical specificities of writing tools aimed at enhancing writing processes (e.g., spelling, revising) and/or at providing writers with automated feedback to improve the implementation of those processes. The tools are described in detail, along with empirical data on their effectiveness in improving one or more aspects of writing. All articles conclude by indicating future directions for further developing and evaluating the tools. This Special Issue represents an important contribution to the field of technology-based writing instruction, in a moment in which online teaching and learning tools have shifted from being an instructional asset to a necessity. We hope that in the future the validation of each tool can be expanded by reaching out to different populations and cultural contexts.

Teaching the craft of written science communication is an arduous task that requires familiarity with disciplinary writing conventions. With the burgeoning of technological advancements, practitioners preparing novice research writers can begin to augment teaching and learning with activities in digital writing environments attuned to the conventions of scientific writing in the disciplines. The Research Writing Tutor (RWT) is one such technology. Grounded in an integrative theoretical framework, it was designed to help students acquire knowledge about the research article genre and develop research writing competence. One of its modules was designed to facilitate revision by providing different forms of automated feedback and scaffolding that are genre-based and discipline-specific. This study explores whether and how the features of the RWT may impact revision while using this module of the tool. Drawing from cognitive writing modeling, this study investigates the behaviors of a multidisciplinary group of 11 graduate-student writers by exploring how they interacted with the RWT's features and how this interaction may create conditions for enhanced revision processes and text modifications. Findings demonstrate promising potential for the use of this automated feedback tool in fostering writers' metacognitive processing during revision. This research adds to theory on cognitive writing models by acknowledging the evolving role of digital environments in writing practices and offering insights into future development of automated tools for genre-based writing instruction.